Enhancing magnetic signals in unexploded ordnances (UXO) detection based on edge-preserved stable downward continuation method

Abstract This paper describes an efficient edge-preserved regularization algorithm for downward continuation of magnetic data in detecting unexploded ordnance (UXO). The magnetic anomalies arising from multi-source UXO can overlap at a height over the ground surface while causative sources may not be readily separated due to low level of signal-to-noise ratio of the observed data. To effectively work the magnetic method in the cleanup stage of contaminated area with UXO, the magnetic anomalies of UXO sources should be enhanced in order to separate the locations of different sources. The stable downward continuation of magnetic data can increase the signal-to-noise ratio, which subsequently causes the separation of UXO sources by enhancing the signals. In this study the researchers formulated the downward continuation as a linear ill-posed deconvolution problem. To obtain a reasonable downward continued field, the proposed filter is stabilized in a Fourier domain to regularize the downward solution using the edge-preserved (or total-variation) algorithm. The L-curve method was used to choose the optimum value of the regularization parameter, which is a trade-off between the misfit and the solution norms in the cost function of optimization problem. A synthetic magnetic field was constructed from isolated multi-source UXO anomalies, the results of which show that the data can be stably downward continued to the ground surface. Likewise, a field data set was provided to demonstrate the capability of the applied method in UXO detection. The results of the synthetic and real case study revealed that the observed magnetic anomalies at a specific height of survey over the ground surface have low amplitude, indeed, the causative UXO sources may not be readily distinguished in detection process, especially anomalies from small UXOs. It was shown that the continued data can enhance the locations of UXOs while small ones are not distinguishable in the primary data

Parametric study and flow characteristics of a new duct for ducted wind turbines system using analytical hierarchy process: numerical & experimental study

This paper aims to study aerodynamic modeling and optimization of the ducts to increase the power efficiency of ducted wind turbines. We design ducted wind turbines based on the features used to determine the sizes and indices of wind tunnels. Many researchers used analytical and numerical methods to select the optimized duct. This study evaluates the effect of design parameters, such as nozzle length, contraction ratio, and outlet diameter, on multiple responses. By applying the analytical hierarchy process (AHP), we find the best design of a duct optimizing the multi-criteria responses. A duct prototype is fabricated to validate the optimal design, and experimental analyses are conducted based on the fabricated duct. A measurement system estimates the pressure distribution in the inlet contraction section; then, a hot-wire sensor investigates wind speed and the flow turbulence in the throat section. A good correlation between calculated data and measured values was found during the estimation of pressure distribution along the inlet contraction wall. Investigation of flow turbulence in the throat section indicates velocity in the duct throat can increase from 2.6 to 2.9 times related to the free flow velocity at different working speeds. Spectral analysis of the flow signal inside the duct shows two peaks in a frequency lower than 32 Hz related to wind tunnel vibration and Gartler vortex. Then, the flow disturbances will not significantly impact the performance of the wind turbine placed inside the duct throat

Association of fear of COVID-19 and preventive behaviors (PB) against COVID-19 in Iran

Introduction: The world is currently experiencing a pandemic of COVID-19. The pandemic may affect physical and mental health. Therefore, this study aims to investigate the fear of COVID-19 and study the relationship between fear of COVID-19 and preventive behaviors against COVID-19. Material and methods: We conducted a web-based cross-sectional study to evaluate the fear of COVID-19 and preventive behaviors against COVID-19 among the volunteer population in Golestan Province, Iran in May 2020 and June 2020. The online questionnaire included the Fear of COVID-19 Scale (FCV-19S) and the prevention behaviors against COVID-19, which are used to assess the fear and prevention behaviors of the population, respectively. The data were presented by mean and frequency. Multiple linear regression analysis was performed to identify factors associated with Fear of COVID-19 at a significant level of 0.05 in Stata 14. Results: A total of 734 of the 900 individuals contacted completed the survey, with a participation rate of 81.5. The mean age of the participants was 33.97 ± 10.68 years and 375 (51.9) were females. The mean Fear of COVID-19 score in the participants was 19.69 ± 5.96. There was a significant positive correlation between Fear of COVID-19 and preventive behaviors (r = 0.19, p < 0.001). Multiple linear regression analysis showed participants with a higher perceived threat of COVID-19, women, married participants, health workers and people with underlying diseases had higher levels of fear of COVID-19. Conclusions: The fear of COVID-19 in Iranian society is high, which indicates the need to pay attention to the mental health in pandemic conditions. Appropriate intervention action can be designed and implemented according to the factors that affect fear. In addition, it should be noted that people with less fear are less likely to observe the COVID-19�s preventative behaviors. © Copyright 2021 Via Medic